EY’s Digital Risk practice is supporting leading Technology, Media & Telecommunications (TMT) companies as they scale cloud-native, AI-enabled, and platform-based operating models. Based in San Francisco, this role sits at the forefront of innovation, working with high-growth and global technology organizations operating on microservices architectures and AI-driven engineering environments. We are seeking a Manager to support risk, compliance, and control transformation across highly automated and continuously evolving ecosystems. This role requires a combination of SOX knowledge, cloud architecture understanding, and familiarity with modern software development practices, including AI-assisted coding and product development lifecycles (PDLC/ SDLC). You will work closely with senior team members and client stakeholders, including finance, technology, and engineering teams, to support the design and implementation of scalable, audit-ready risk and compliance frameworks within complex technology environments. Your key responsibilities As a Manager in our Digital Risk practice, you will support the delivery of complex Digital Risk engagements, owning key workstreams and contributing to overall program execution across cloud-native environments. You will work closely with senior leadership and client stakeholders to drive risk and control initiatives within modern technology ecosystems. In this role, you will: Execute and manage workstreams across cloud platforms, microservices architectures, and AI-enabled development environments, including risk assessments, control design, and testing activities Support client engagement teams by working directly with stakeholders (e.g., finance, IT, engineering) to deliver clear, actionable insights and recommendations Oversee day-to-day delivery, including coordination of team members, tracking progress, and ensuring quality and timeliness of deliverables Contribute to engagement performance, including resource management, status tracking, and supporting budgeting and forecasting activities Provide technical guidance within your areas of expertise, supporting team members on cloud, platform, and engineering risk considerations Design and evaluate controls across DevOps, CI/ CD pipelines, SDLC/ PDLC processes, and distributed platforms, including APIs, microservices, data environments, and AI-enabled systems Skills and attributes for success Demonstrate strong understanding of cloud-native architectures, distributed systems, and modern engineering practices, applying that knowledge to support the design and assessment of scalable control solutions. Exhibit an AI-aware risk mindset, with the ability to identify risks introduced by AI-assisted development and automated engineering workflows. Demonstrate architecture fluency, interpreting system interactions and data flows to support control design and evaluation. Build engineering credibility, partnering effectively with DevOps, platform, and data teams within complex environments. Apply your TMT industry knowledge to understand evolving risks within high-growth, technology-driven organizations. Communicate clearly and effectively, translating technical risk concepts into practical business insights for client stakeholders while contributing to overall delivery quality. Operate with attention to detail and accountability, managing competing priorities while contributing to high-quality outcomes and continuous improvement. To qualify for the role you must have A bachelor’s or master’s degree in business, accounting, computer science, engineering, or a related field A minimum of 5 years of experience in Digital Risk, IT risk, or technology consulting, with exposure to TMT sector clients Hands-on experience in cloud platforms (e.g., AWS), microservices architectures, DevOps/ CI/ CD, SDLC/ PDLC, and distributed systems Experience supporting: IT general controls (ITG - Cs) and automated control environments Risk assessments, control testing, and control design activities Technology risk engagements within cloud-native or distributed environments Understanding of how regulatory and control frameworks (e.g., SOX, internal controls) apply within modern engineering environments Exposure to data platforms and AI-enabled development environments Willingness to travel at least 50%, including client-site travel. Flexibility to work extended hours as needed. Ideally, you’ll also have Relevant certifications such as CPA, CISA, CISSP, CISM; cloud certifications (e.g., AWS) or AI-related certifications are a plus